DETECTION OF VENTILATION SUFFICIENCY

• US 20140007878A1
• Filed: 03/15/2012
• Published: 01/09/2014
• Est. Priority Date: 03/23/2011
• Status: Active Grant

• Current Assignee: ResMed Pty Ltd. (ResMed Incorporated)
• Original Assignee: Resmed Limited (ResMed Incorporated)
• Inventors: Armitstead, Jeffrey Peter, Ramanan, Dinesh
• Granted Patent: US 10,342,939 B2
• Time in Patent Office: Days
• US Class Current: 128/204.23
• CPC Class Codes: A61B 5/083 Measuring rate of metabolism by using breath test, e.g. measuring rate of oxygen consumption
• CPC Class Codes: A61B 5/087 Measuring breath flow
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61M 16/0051 with alarm devices
• CPC Class Codes: A61M 16/0057 Pumps therefor
• CPC Class Codes: A61M 16/0069 the speed thereof being controlled by respiratory parameters, e.g. by inhalation
• CPC Class Codes: A61M 16/024 including calculation means, e.g. using a processor
• CPC Class Codes: A61M 2016/0027 pressure meter
• CPC Class Codes: A61M 2016/0039 in the inspiratory circuit
• CPC Class Codes: A61M 2205/15 Detection of leaks
• CPC Class Codes: A61M 2205/18 with alarm
• CPC Class Codes: A61M 2205/3553 remote, e.g. between patient's home and doctor's office
• CPC Class Codes: A61M 2205/502 User interfaces, e.g. screens or keyboards
• CPC Class Codes: A61M 2230/435 partial O2 pressure (P-O2)

Abstract

Automated methods provide a ventilation sufficiency assessment to evaluate patient respiration. In some embodiments, a ventilation histogram maybe determined from a measure of patient respiratory flow. Based on the histogram or associated ventilation data, hypoventilation or hyperventilation occurrences may be detected. For example, a kurtosis index and/or skewness index may be calculated with the data associated with the ventilation histogram and may be evaluated as an indication of hypoventilation or hyperventilation. An assessment of the number of peaks and other features of the ventilation histogram, such as in the case of a bimodal ventilation histogram, may be implemented to detect an occurrence of ventilation insufficiency or sufficiency. The detection methodologies may be implemented by a specific purpose computer, a detection device that measures a respiratory airflow or a respiratory treatment apparatus that provides a respiratory treatment regime based on the detected ventilation sufficiency.

Claims

1. A method for controlling a processor to assess sufficiency of ventilation from a measured flow of breathable gas, the method of the processor comprising:

accessing a measure of a flow of breathable gas representative of patient respiration;

deriving measures of ventilation from the measure of flow; and

determining, with a processor, a histogram based on the measures of ventilation.

2. The method of claim 1 further comprising displaying a graph of the histogram on a visual display device.

3. The method of claim 1 or 2 wherein the histogram represents a frequency distribution of ventilation values taken over the course of a treatment session, each ventilation value comprising a measure of volume over a time interval, the time interval being shorter than the time of the treatment session.

4. The method of claim 3 wherein the time interval is on an order of a minute and the time of the treatment session is on an order of hours.

5. The method of any one of the preceding claims further comprising:

processing, in the processor, data associated with the histogram to calculate a skewness index;

comparing the skewness index to a threshold; and

indicating hypoventilation based on the comparison.

6. The method of any one of the preceding claims further comprising:

processing, in the processor, data associated with the histogram to calculate a skewness index;

comparing the skewness index to a threshold; and

indicating hyperventilation based on the comparison.

7. The method of any one of the preceding claims further comprising:

processing, in the processor, data associated with the histogram to detect a number of peaks of the histogram; and

indicating a presence or absence of hypoventilation based on the number of detected peaks.

8. The method of any one of the preceding claims further comprising:

processing, in the processor, data associated with the histogram to determine a kurtosis index;

comparing the kurtosis index to a threshold; and

indicating a presence or absence of hypoventilation based on the comparison.

9. The method of any one of the preceding claims further comprising controlling, with the processor, measuring of the flow of breathable gas with a flow sensor.

10. The method of any one of the preceding claims further comprising processing data representing the histogram to generate a hypoventilation indicator, the indicator representing an occurrence of an event of hypoventilation.

11. The method of claim 10 wherein the hypoventilation indicator comprises a probability value.

12. The method of claim 10 or 11 wherein the processing comprises a detection of peaks of the histogram.

13. The method of claim 12 wherein the processing comprises calculating a distance between peaks of the histogram and transforming the distance into a probability space.

14. The method of claim 12 or 13 wherein the processing comprises calculating a gradient between peaks of the histogram.

15. The method of claim 14 wherein the processing comprises calculating an area with respect to the gradient and transforming the area into a probability space.

16. The method of claim any of claims 10 to 15 wherein the processing comprises calculating a set of features of the histogram and generating the indicator based on an evaluation of the set of features.

17. The method of claim 16 wherein the set of features comprises two or more of the following features:

a gradient between two largest peaks, a gradient between a largest peak and a center point, a gradient between a second largest peak and a center point, an area between two largest peaks, an area between a largest peak and a center point, an area between a second largest peak and a center point, a shape feature, kurtosis value and skewness value.

18. The method of any of the preceding claims further comprising determining a measure of leak and distinguishing measures of ventilation for the histogram based on the measure of leak.

19. The method of any of the preceding claims further comprising determining a measure of ventilation stability and distinguishing measures of ventilation for the histogram based on the measure of stability.

20. The method of claim 19 wherein the determining the measure of ventilation stability comprises any of one or more of a detection of an awake period, an apnea event, a periodic breathing event and an arousal event.

21. A ventilation assessment apparatus comprising:

a controller having at least one processor to access data representing a measured flow of breathable gas attributable to patient respiration, the controller being further configured to (a) derive measures of ventilation from the measure of flow, and (b) determine a histogram based on the measures of ventilation.

22. The apparatus of claim 21 wherein the controller is further configured to display a graph of the histogram on a visual display device.

23. The apparatus of claim 21 or 22 wherein the histogram represents a frequency distribution of ventilation values taken over the course of a treatment session, each ventilation value comprising a measure of volume over a time interval, the time interval being shorter than the time of the treatment session.

24. The apparatus of claim 23 wherein the time interval is on an order of a minute and the time of the treatment session is on an order of hours.

25. The apparatus of any one of claims 21 to 21 wherein the controller is further configured to:

process data associated with the histogram to calculate a skewness index;

compare the skewness index to a threshold; and

indicate an occurrence of hypoventilation based on the comparison.

26. The apparatus of any one of claims 21 to 22 wherein the controller is further configured to:

process data associated with the histogram to calculate a skewness index;

compare the skewness index to a threshold; and

indicate an occurrence of hyperventilation based on the comparison.

27. The apparatus of any one of claims 21 to 23 wherein the controller is further configured to:

process data associated with the histogram to detect a number of peaks of the histogram; and

indicate a presence or absence of hypoventilation based on the number of detected peaks.

28. The apparatus of any one of claims 21 to 24 wherein the controller is further configured to:

process data associated with the histogram to determine a kurtosis index;

compare the kurtosis index to a threshold; and

indicate a presence or absence of hypoventilation based on the comparison.

29. The apparatus of any one of claims 21 to 25 further comprising a flow sensor, and wherein the controller is further configured to control measuring of the flow of breathable gas with the flow sensor.

30. The apparatus of claim 29 further comprising:

a flow generator configured to produce a breathable gas for a patient at a pressure above atmospheric pressure;

wherein the controller is further configured to control the flow generator to produce the breathable gas according to a pressure therapy regime based on an assessment of any one or more of (a) the histogram, (b) a number of peaks of the histogram, (c) a kurtosis index determined from data associated with the histogram and (d) a skewness index determined from data associated with the histogram.

31. The apparatus of any one of claims 21 to 27 wherein the controller is configured to process data representing the histogram to generate a hypoventilation indicator, the indicator representing an occurrence of an event of hypoventilation.

32. The apparatus of claim 31 wherein the hypoventilation indicator comprises a probability value.

33. The apparatus of claim 31 or 32 wherein the controller is configured to detect peaks of the histogram.

34. The apparatus of claim 33 wherein the controller is configured to calculate a distance between peaks of the histogram and transforming the distance into a probability space.

35. The apparatus of claim 33 or 34 wherein the controller is configured to calculate a gradient between peaks of the histogram.

36. The apparatus of claim 35 wherein the controller is configured to calculate an area with respect to the gradient and transform the area into a probability space.

37. The apparatus of claim any of claims 31 to 33 wherein the controller is configured to calculate a set of features of the histogram and to generate the indicator based on an evaluation of the set of features.

38. The apparatus of claim 37 wherein the set of features comprises two or more of the following features:

a gradient between two largest peaks, a gradient between a largest peak and a center point, a gradient between a second largest peak and a center point, an area between two largest peaks, an area between a largest peak and a center point, an area between a second largest peak and a center point, a shape feature, kurtosis value and skewness value.

39. The apparatus of any one of claims 21 to 38 wherein the controller is configured to determine a measure of leak and to distinguish the measures of ventilation for the histogram based on the measure of leak.

40. The apparatus of any one of claims 21 to 39 wherein the controller is configured to determine a measure of ventilation stability and to distinguish the measures of ventilation for the histogram based on the measure of stability.

41. The apparatus of claim 40 wherein the controller determines the measure of ventilation stability by detecting any of one, or more of an awake period, an apnea event, a periodic breathing event and an arousal event.

45. The system of claim any one of claims 42 to 38 further comprising means for evaluating a number of histogram peaks from data associated with the histogram to detect an occurrence of hypoventilation.

46. The system of claim any one of claims 42 to 39 further comprising means for evaluating a kurtosis index based on data associated with the histogram to detect a presence or absence of hypoventilation.

47. The system of claim any one of claims 42 to 40 further comprising means for generating a breathable gas for a patient at a pressure above atmospheric pressure based on an assessment of any one or more of (a) the histogram, (b) a number of peaks of the histogram, (c) a kurtosis index determined from data associated with the histogram and (d) a skewness index determined from data associated with the histogram.

48. The system of any one of claims 42 to 41 further comprising means for processing data representing the histogram to generate a hypoventilation indicator, the indicator representing an occurrence of an event of hypoventilation.

49. The system of claim 48 wherein the hypoventilation indicator comprises a probability value.

50. The system of claim 48 or 49 wherein further comprising means for detecting peaks of the histogram.

51. The system of claim 50 further comprising means for calculating a distance between peaks of the histogram and transforming the distance into a probability space.

52. The system of claim 50 or 51 further comprising means for calculating a gradient between peaks of the histogram.

53. The system of claim 52 further comprising means for calculating an area with respect to the gradient and transforming the area into a probability space.

54. The system of claim any of claims 31 to 33 further comprising means for calculating a set of features of the histogram and generating the indicator based on an evaluation of the set of features.

55. The system of claim 37 wherein the set of features comprises two or more of the following features:

a gradient between two largest peaks, a gradient between a largest peak and a center point, a gradient between a second largest peak and a center point, an area between two largest peaks, an area between a largest peak and a center point, an area between a second largest peak and a center point, a shape feature, kurtosis value and skewness value.

42. A ventilation assessment system comprising:

means for measuring a flow of breathable gas attributable to patient respiration during a treatment session,

means for deriving measures of ventilation from the measure of flow, and

means for determining a histogram based on the measures of ventilation.

43. The system of claim 42 further comprising means for displaying a visual graph of the histogram.

44. The system of claim 42 or 43 further comprising means for evaluating a skewness index based on data associated with the histogram to detect an occurrence of hypoventilation or hyperventilation.

56. The system of any one of claims 42 to 55 further comprising a leak detector to determine a measure of leak, wherein the system is configured to distinguish the measures of ventilation for the histogram based on the measure of leak.

57. The system of any one of claims 42 to 56 further comprising ventilation stability detector, wherein the system is configured to distinguish the measures of ventilation for the histogram based on the measure of stability.

58. The system of claim 57 wherein the ventilation stability detector includes means for detecting one or more of an awake period, an apnea event, a periodic breathing event and an arousal event.